Ask a customer to fill out an online survey and he’ll tell you he’s a healthy eater. Correlate his survey responses with his actual shopping behaviours, however, and you’ll draw a different conclusion. For a whole host of reasons, people aren’t going to come right out and say just what they want. They’re coming to you for a retail experience, not for a reality show confessional.
In a sense, however, they’re confessing to you anyway: it’s all right there in their data – what they buy, when they buy it, how often they buy it. And here is the best part – they are only telling it to you. You have their data and no one else does. Not the brand name retailer who spends a fortune advertising on TV, and not your competitor.
Which begs the question: How well are you listening to your customers? Do you know just what brings them into your shop or draws them to your website? There had to be a reason, however fantastic or prosaic. What was it? More to the point, are there others like them? Do you know? No question, we’re all special, idiosyncratic, and absolutely unique, but – as any sociologist or marketing analyst will tell you – we likewise tend to cluster into certain segments, groups, or cohorts. So would the same things that drew Jimmy into your store also resonate with other, Jimmy-like customers? The clues are right there in their data: in what, when, where, and how often they buy or interact with you.
In the past, the best way to figure out what customers truly wanted was to, you know, talk with them. In the age of data, it’s tempting to think of conversation as inefficient, and unnecessary. if I can track what Jane does in different contexts, if I can determine that what she’s saying on social media is at odds with what she’s doing in practice, I can gain profound insight into Jane as a customer. This ability to identify, correlate, and analyse customer behavior is unprecedented. It’s less expensive than you think, and it’s getting more powerful and even easier to do all the time. But this also brings with it a great responsibility.
Because I also run the risk of really, really creeping Jane out. This is what happened to Target in 2012, when its habit of using analytics to identify and (stealth) market to pregnant women caused a major incident in the United States. Target’s analytics gurus identified products that pregnant women tend to buy; once a shopper bought them, Target bombarded her with targeted ads.
This kind of thing isn’t just creepy, it’s insidious. It’s one thing to market to people, it’s quite another thing to manipulate them. Because of the way we as human beings are wired, however, advanced analytic technologies will make it increasingly possible to do just this. If we’re going to use analytics responsibly, it’s incumbent upon us to work to build relationships with our customers: to listen actively and empathically to what they say and, yes, to discern what they don’t say.
Above all, to respect them as human beings. People like a good listener: they like to be heard, they like to be validated, and – done rightly – they appreciate tailored, personalised interactions.
They just don’t want to be creeped out. Can you blame them?
This story was originally published in NZ Retail magazine issue 738, June / July 2015.